Combinational usage of next generation sequencing and qPCR for the analysis of tumor samples

Research Trends and Development Dynamics of qPCR-based Biomarkers: A Comprehensive Bibliometric Analysis

Quantitative polymerase chain reaction (qPCR) is a vital molecular technique for biomarker detection; however, its clinical application is impeded by the scarcity of robust biomarkers and the inherent limitations of the technology. This study conducted a bibliometric analysis of 4063 qPCR-based biomarker studies sourced from the Web of Science (WOS) database, employing VOSviewer and CiteSpace to generate multi-dimensional structural insights into this field. The results reveal a growing trend in research within this domain, with gene expression analysis playing a central role in the identification of potential biomarkers. Among these, cancer-related biomarkers are the most prominent, while research on biomarkers for other diseases remains limited. Liquid biopsy biomarkers, including microRNA (miRNA), circulating free DNA (cfDNA), and circulating tumor DNA (ctDNA), are increasingly being explored. The integration of bioinformatics, omics analysis, and high-throughput technologies with qPCR is accelerating biomarker discovery. Furthermore, large-scale parallel sequencing is emerging as a potential alternative to relative quantification and microarray techniques. Nevertheless, qPCR remains essential for validating specific biomarkers, and further standardization of its protocols is necessary to enhance reliability. This study provides a systematic analysis of qPCR-based biomarker research and underscores the need for future technological integration and standardization to facilitate broader clinical applications.

Anoikis-Related Genes Impact Prognosis and Tumor Microenvironment in Bladder Cancer

Anoikis tolerance is an important biological process of tumor colonization and metastasis outside the primary tumor. Recent research has progressively elucidated the function and underlying mechanisms of anoikis in the metastasis of various solid tumors. Nevertheless, the specific mechanisms of anoikis in bladder cancer and its consequent effects on the tumor immune microenvironment remain ambiguous. In this study, we developed an anoikis score based on five genes (ETV7, NGF, SCD, LAMC1, and CASP6) and categorized subjects into high and low-risk groups using the median score from the TCGA database. Our findings indicate that SCD enhances the proliferation of bladder cancer cells in vitro. Furthermore, integrating the anoikis score with clinicopathological features to construct a prognostic nomogram demonstrated precision in assessing patient outcomes. Immune cell analysis revealed elevated infiltration levels of Treg cells and M2 macrophages in the high anoikis score group, whereas CD8+ T cell levels were reduced. This study highlights the importance of anoikis score in predicting patient prognosis, immune cell infiltration, and drug response, which may provide a treatment modality worth exploring in depth for the study of bladder cancer.

A fuzzy method for RNA-Seq differential expression analysis in presence of multireads

Background

When the reads obtained from high-throughput RNA sequencing are mapped against a reference database, a significant proportion of them - known as multireads - can map to more than one reference sequence. These multireads originate from gene duplications, repetitive regions or overlapping genes. Removing the multireads from the mapping results, in RNA-Seq analyses, causes an underestimation of the read counts, while estimating the real read count can lead to false positives during the detection of differentially expressed sequences.

Results

We present an innovative approach to deal with multireads and evaluate differential expression events, entirely based on fuzzy set theory. Since multireads cause uncertainty in the estimation of read counts during gene expression computation, they can also influence the reliability of differential expression analysis results, by producing false positives. Our method manages the uncertainty in gene expression estimation by defining the fuzzy read counts and evaluates the possibility of a gene to be differentially expressed with three fuzzy concepts: over-expression, same-expression and under-expression. The output of the method is a list of differentially expressed genes enriched with information about the uncertainty of the results due to the multiread presence.

We have tested the method on RNA-Seq data designed for case-control studies and we have compared the obtained results with other existing tools for read count estimation and differential expression analysis.

Conclusions

The management of multireads with the use of fuzzy sets allows to obtain a list of differential expression events which takes in account the uncertainty in the results caused by the presence of multireads. Such additional information can be used by the biologists when they have to select the most relevant differential expression events to validate with laboratory assays. Our method can be used to compute reliable differential expression events and to highlight possible false positives in the lists of differentially expressed genes computed with other tools.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1195-2) contains supplementary material, which is available to authorized users.

Transcriptome Analysis of Targeted Mouse Mutations Reveals the Topography of Local Changes in Gene Expression

The unintended consequences of gene targeting in mouse models have not been thoroughly studied and a more systematic analysis is needed to understand the frequency and characteristics of off-target effects. Using RNA-seq, we evaluated targeted and neighboring gene expression in tissues from 44 homozygous mutants compared with C57BL/6N control mice. Two allele types were evaluated: 15 targeted trap mutations (TRAP); and 29 deletion alleles (DEL), usually a deletion between the translational start and the 3' UTR. Both targeting strategies insert a bacterial beta-galactosidase reporter (LacZ) and a neomycin resistance selection cassette. Evaluating transcription of genes in +/- 500 kb of flanking DNA around the targeted gene, we found up-regulated genes more frequently around DEL compared with TRAP alleles, however the frequency of alleles with local down-regulated genes flanking DEL and TRAP targets was similar. Down-regulated genes around both DEL and TRAP targets were found at a higher frequency than expected from a genome-wide survey. However, only around DEL targets were up-regulated genes found with a significantly higher frequency compared with genome-wide sampling. Transcriptome analysis confirms targeting in 97% of DEL alleles, but in only 47% of TRAP alleles probably due to non-functional splice variants, and some splicing around the gene trap. Local effects on gene expression are likely due to a number of factors including compensatory regulation, loss or disruption of intragenic regulatory elements, the exogenous promoter in the neo selection cassette, removal of insulating DNA in the DEL mutants, and local silencing due to disruption of normal chromatin organization or presence of exogenous DNA. An understanding of local position effects is important for understanding and interpreting any phenotype attributed to targeted gene mutations, or to spontaneous indels.

qRT-PCR evaluation of the transcriptional response of zebra mussel to heavy metals

Background

The transcriptional response of adult zebra mussels (Dreissena polymorpha) to heavy metals (mercury, copper, and cadmium) was analyzed by quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) to study the coordinated regulation of different metal-, oxidative stress- and xenobiotic defence-related genes in gills and digestive gland. Regulatory network analyses allowed the comparison of this response between different species and taxa.

Results

Chemometric analyses allowed identifying the effects of these metals clearly separating control and treated samples of both tissues. Interactions between the different genes, either in the same or between both tissues, were analysed to identify correlations and to propose stress-related genes’ regulatory networks. These networks were finally compared with existing data from human, mouse, zebrafish, Drosophila and the roundworm to evaluate their mechanistically-known response to metals (and to stressors in general) with the correlations observed in the still poorly-known, invasive zebra mussel.

Conclusions

Our analyses found a general conservation of regulation genes and of their interactions among the different considered species, and may serve as a guide to extrapolate regulatory data from model species to lesser-known environmentally (or medically) relevant species.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1567-4) contains supplementary material, which is available to authorized users.

Examining the effects of nuclear GPCRs on gene expression using isolated nuclei

The measurement of changes in the transcriptome is a common end point for various pathologic and pharmacologic studies. In recent years, with the discovery of a host of potential pharmacologic targets located directly on the nuclear membrane, the need to assess their potential control over the transcriptome has arisen. Here we present techniques for assessing changes in gene expression in isolated nuclei in response to stimulation by endogenous GPCRs on the nuclear membrane.

Trp63 is regulated by STAT5 in mammary tissue and subject to differentiation in cancer

Transformation-related protein 63 (Trp63), the predominant member of the Trp53 family, contributes to epithelial differentiation and is expressed in breast neoplasia. Trp63 features two distinct promoters yielding specific mRNAs encoding two major TRP63 isoforms, a transactivating transcription factor and a dominant negative isoform. Specific TRP63 isoforms are linked to cell cycle arrest, apoptosis, survival, and epithelial mesenchymal transition (EMT). Although TRP63 overexpression in cultured cells is used to elucidate functions, little is known about Trp63 regulation in normal and cancerous mammary tissues. This study used ChIP-seq to interrogate transcription factor binding and histone modifications of the Trp63 locus in mammary tissue and RNA-seq and immunohistochemistry to gauge gene expression. H3K4me2 and H3K4me3 marks coincided only with the proximal promoter, supporting RNA-seq data showing the predominance of the dominant negative isoform. STAT5 bound specifically to the Trp63 proximal promoter and Trp63 mRNA levels were elevated upon deleting Stat5 from mammary tissue, suggesting its role as a negative regulator. The dominant negative TRP63 isoform was localized to nuclei of basal mammary epithelial cells throughout reproductive cycles and retained in a majority of the triple-negative cancers generated from loss of full-length Brca1. Increased expression of dominant negative isoforms was correlated with developmental windows of increased progesterone receptor binding to the proximal Trp63 promoter and decreased expression during lactation was correlated with STAT5 binding to the same region. TRP63 is present in the majority of triple-negative cancers resulting from loss of Brca1 but diminished in less differentiated cancer subtypes and in cancer cells undergoing EMT.

Application of SNP microarrays to the genome-wide analysis of chromosomal instability in premalignant airway lesions

Chromosomal instability is central to the process of carcinogenesis. The genome-wide detection of somatic chromosomal alterations (SCA) in small premalignant lesions remains challenging because sample heterogeneity dilutes the aberrant cell information. To overcome this hurdle, we focused on the B allele frequency data from single-nucleotide polymorphism microarrays (SNP arrays). The difference of allelic fractions between paired tumor and normal samples from the same patient (delta-θ) provides a simple but sensitive detection of SCA in the affected tissue. We applied the delta-θ approach to small, heterogeneous clinical specimens, including endobronchial biopsies and brushings. Regions identified by delta-θ were validated by FISH and quantitative PCR in heterogeneous samples. Distinctive genomic variations were successfully detected across the whole genome in all invasive cancer cases (6 of 6), carcinoma in situ (3 of 3), and high-grade dysplasia (severe or moderate; 3 of 11). Not only well-described SCAs in lung squamous cell carcinoma, but also several novel chromosomal alterations were frequently found across the preinvasive dysplastic cases. Within these novel regions, losses of putative tumor suppressors (RNF20 and SSBP2) and an amplification of RASGRP3 gene with oncogenic activity were observed. Widespread sampling of the airway during bronchoscopy demonstrated that field cancerization reflected by SCAs at multiple sites was detectable. SNP arrays combined with delta-θ analysis can detect SCAs in heterogeneous clinical sample and expand our ability to assess genomic instability in the airway epithelium as a biomarker of lung cancer risk.

Veterinary and human biobanking practices: enhancing molecular sample integrity

Animal models have historically informed veterinary and human pathophysiology. Next-generation genomic sequencing and molecular analyses using analytes derived from tissue require integrative approaches to determine macroanalyte integrity as well as morphology for imaging algorithms that can extend translational applications. The field of biospecimen science and biobanking will play critical roles in tissue sample collection and processing to ensure the integrity of macromolecules, aid experimental design, and provide more accurate and reproducible downstream genomic data. Herein, we employ animal experiments to combine protein expression analysis by microscopy with RNA integrity number and quantitative measures of morphologic changes of autolysis. These analyses can be used to predict the effect of preanalytic variables and provide the basis for standardized methods in tissue sample collection and processing. We also discuss the application of digital imaging with quantitative RNA and tissue-based protein measurements to show that genomic methods augment traditional in vivo imaging to support biospecimen science. To make these observations, we have established a time course experiment of murine kidney tissues that predicts conventional measures of RNA integrity by RIN analysis and provides reliable and accurate measures of biospecimen integrity and fitness, in particular for time points less than 3 hours post-tissue resection.

Detection of Circulating Tumour Cells from Blood of Breast Cancer Patients via RT-qPCR

Breast cancer is still the most frequent cause of cancer-related death in women worldwide. Often death is not caused only by the primary tumour itself, but also by metastatic lesions. Today it is largely accepted, that these remote metastases arise out of cells, which detach from the primary tumour, enter circulation, settle down at secondary sites in the body and are called Circulating Tumour Cells (CTCs). The occurrence of such minimal residual diseases in the blood of breast cancer patients is mostly linked to a worse prognosis for therapy outcome and overall survival. Due to their very low frequency, the detection of CTCs is, still a technical challenge. RT-qPCR as a highly sensitive method could be an approach for CTC-detection from peripheral blood of breast cancer patients. This assumption is based on the fact that CTCs are of epithelial origin and therefore express a different gene panel than surrounding blood cells. For the technical approach it is necessary to identify appropriate marker genes and to correlate their gene expression levels to the number of tumour cells within a sample in an in vitro approach. After that, samples from adjuvant and metastatic patients can be analysed. This approach may lead to new concepts in diagnosis and treatment.